Large multivariate data sets still challenge visualization techniques and their interactive capabil-ities. In this paper we present a new faster formulation of a high precision projection technique that allows much larger data sets to be handled and interacted with. By using this novel approach, named Piecewise Least Square Projection (P-LSP), we provide new and effective ways of exploring the data set through its feature space. The paper shows the use of P-LSP to help data selection by the user during exploration using coherence amongst data items. Examples are shown for images and for volumes as large as 1,000,000 voxels, with as many as 14 variables per voxel, although the technique can also be used for any data set for which a reasonabl...
Fig. 1. Traditional projection techniques can yield overplot and lose context of the original data d...
A new method for assisting with the visualization of large multidimensional datasets is proposed. We...
Dimensionality Reduction, in particular, projection-based methods transform the data to a lower-dime...
Most multidimensional projection techniques rely on distance (dissimilarity) information between dat...
Multidimensional projection has emerged as an important visualization tool in applications involving...
Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to...
Multidimensional projection is emerging as an important visualization tool in applications involving...
We propose a multidimensional visualization technique, named Viz3D, that creates a 3D representation...
Multidimensional projections map data points, defined in a high-dimensional data space, into a 1D, 2...
The problem of projecting multidimensional data into lower dimensions has been pursued by many resea...
In this paper, we present an effective and scalable system for multivariate volume data visualizatio...
Abstract—In this paper, we present an effective and scalable system for multivariate volume data vis...
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection ...
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection ...
Parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight i...
Fig. 1. Traditional projection techniques can yield overplot and lose context of the original data d...
A new method for assisting with the visualization of large multidimensional datasets is proposed. We...
Dimensionality Reduction, in particular, projection-based methods transform the data to a lower-dime...
Most multidimensional projection techniques rely on distance (dissimilarity) information between dat...
Multidimensional projection has emerged as an important visualization tool in applications involving...
Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to...
Multidimensional projection is emerging as an important visualization tool in applications involving...
We propose a multidimensional visualization technique, named Viz3D, that creates a 3D representation...
Multidimensional projections map data points, defined in a high-dimensional data space, into a 1D, 2...
The problem of projecting multidimensional data into lower dimensions has been pursued by many resea...
In this paper, we present an effective and scalable system for multivariate volume data visualizatio...
Abstract—In this paper, we present an effective and scalable system for multivariate volume data vis...
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection ...
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection ...
Parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight i...
Fig. 1. Traditional projection techniques can yield overplot and lose context of the original data d...
A new method for assisting with the visualization of large multidimensional datasets is proposed. We...
Dimensionality Reduction, in particular, projection-based methods transform the data to a lower-dime...